Source sector and fuel contributions to ambient PM2.5 and attributable mortality across multiple spatial scales

Mortality Attributable to Ambient Air Pollution: A Review of Global Estimates

Since the publication of the first epidemiological study to establish the connection between long-term exposure to atmospheric pollution and effects on human health, major efforts have been dedicated to estimate the attributable mortality burden, especially in the context of the Global Burden of Disease (GBD). In this work, we review the estimates of excess mortality attributable to outdoor air pollution at the global scale, by comparing studies available in the literature. We find large differences between the estimates, which are related to the exposure response functions as well as the number of health outcomes included in the calculations, aspects where further improvements are necessary. Furthermore, we show that despite the considerable advancements in our understanding of health impacts of air pollution and the consequent improvement in the accuracy of the global estimates, their precision has not increased in the last decades. We offer recommendations for future measurements and research directions, which will help to improve our understanding and quantification of air pollution-health relationships.

Impact of lowering fine particulate matter from major emission sources on mortality in Canada: A nationwide causal analysis

Emissions of fine particulate matter (PM_2.5) from human activities have been linked to substantial disease burdens, but evidence regarding how reducing PM_2.5 at its sources would improve public health is sparse. We followed a population-based cohort of 2.7 million adults across Canada from 2007 through 2016. For each participant, we estimated annual mean concentrations of PM_2.5 and the fractional contributions to PM_2.5 from the five leading anthropogenic sources at their residential address using satellite observations in combination with a global atmospheric chemistry transport model. For each source, we estimated the causal effects of six hypothetical interventions on 10-y nonaccidental mortality risk using the parametric g-formula, a structural causal model. We conducted stratified analyses by age, sex, and income. This cohort would have experienced tangible health gains had contributions to PM_2.5 from any of the five sources been reduced. Compared with no intervention, a 10% annual reduction in PM_2.5 contributions from transportation and power generation, Canada's largest and fifth-largest anthropogenic sources, would have prevented approximately 175 (95%CI: 123-226) and 90 (95%CI: 63-117) deaths per million by 2016, respectively. A more intensive 50% reduction per year in PM_2.5 contributions from the two sources would have averted 360 and 185 deaths per million, respectively, by 2016. The potential health benefits were greater among men, older adults, and low-income earners. In Canada, where PM_2.5 levels are among the lowest worldwide, reducing PM_2.5 contributions from anthropogenic sources by as little as 10% annually would yield meaningful health gains.

Tracking short-term health impacts attributed to ambient PM2.5 and ozone pollution in Chinese cities: an assessment integrates daily population

Joint and synergistic control of PM_2.5 and ozone pollution is an urgent need in China and a global-widely concerned issue. Health impact assessment could provide a comprehensive perspective for PM_2.5-ozone coordinated control strategies. For a detailed understanding of the seasonality and regionality of the health impacts attributed to PM_2.5 and ozone in China, this study extended the classic health impact function by daily population and assessed the short-term (daily) health impacts in 335 Chinese cities in 2021. Population migration indexes from Baidu were introduced to estimate the cities' daily population. Using this method, we quantitatively investigated the influence of population on short-term health impact assessment and identified which was significant in the Pearl River Delta (PRD) region and other populous cities. Although the annual sums of PM_2.5- and ozone-related daily health impacts were close for all Chinese cities, the PM_2.5-related health impact was equivalent to 333.96% and 32.07% of that ozone-related, during the cold and warm periods. The correlation and local spatial association analysis found significant city-specific and city-cluster associations of daily health impacts during the warm period and in Beijing-Tianjin-Hebei and surrounding regions (BTHS) and the Yangtze River Delta (YRD). Policymakers could promote period- and pollutant-targeted control actions for the major city groups, especially the BTHS, YRD, and PRD. Our methods and findings investigated the various influences of the population on short-term health impact assessment and proposed the PM_2.5-ozone collaborative control idea for key regions and city groups.

Reduced inequality in ambient and household PM2.5 exposure in China

The society has high concerns on the inequality that people are disproportionately exposed to ambient air pollution, but with more time spent indoors, the disparity in the total exposure considering both indoor and outdoor exposure has not been explored; and with the socioeconomical development and efforts in fighting against air pollution, it is unknown how the exposure inequality changed over time. Based on the city-level panel data, this study revealed the Concentration Index (C) in ambient PM_2.5 exposure inequality was positive, indicating the low-income group exposed to lower ambient PM_2.5; however, the total PM_2.5 exposure was negatively correlated with the income, showing a negative C value. The low-income population exposed to high PM_2.5 associated with larger contributions of indoor exposure from the residential emissions. The total PM_2.5 exposure caused 1.13 (0.63-1.73) million premature deaths in 2019, with only 14 % were high-income population. The toughest-ever air pollution countermeasures have reduced ambient PM_2.5 exposures effectively that, however, benefited the rich population more than the others. The transition to clean household energy sources significantly affected on indoor air quality improvements, as well as alleviation of ambient air pollution, resulting in notable reductions of the total PM_2.5 exposure and especially benefiting the low-income groups. The negative C values decreased from 2000 to 2019, indicating a significantly reducing trend in the total PM_2.5 exposure inequality over time.

Air quality impacts of crop residue burning in India and mitigation alternatives

Crop residue burning contributes to poor air quality and imposes a health burden on India. Despite government bans and other interventions, this practice remains widespread. Here we estimate the impact of changes in agricultural emissions on air quality across India and quantify the potential benefit of district-level actions using an adjoint modeling approach. From 2003 to 2019, we find that agricultural residue burning caused 44,000-98,000 particulate matter exposure-related premature deaths annually, of which Punjab, Haryana, and Uttar Pradesh contribute 67-90%. Due to a combination of relatively high downwind population density, agricultural output, and cultivation of residue-intensive crops, six districts in Punjab alone contribute to 40% of India-wide annual air quality impacts from residue burning. Burning two hours earlier in Punjab alone could avert premature deaths up to 9600 (95% CI: 8000-11,000) each year, valued at 3.2 (95% CI: 0.49-7.3) billion US dollars. Our findings support the use of targeted and potentially low-cost interventions to mitigate crop residue burning in India, pending further research regarding cost-effectiveness and feasibility.

Subnational implications from climate and air pollution policies in India’s electricity sector

Emissions of greenhouse gases and air pollutants in India are important contributors to climate change and health damages. This study estimates current emissions from India’s electricity sector and simulates the state-level implications of climate change and air pollution policies. We find that (i) a carbon tax results in little short-term emissions reductions because there is not enough dispatchable lower emission spare capacity to substitute coal; (ii) moving toward regional dispatch markets rather than state-level dispatch decisions will not lead to emissions reductions; (iii) policies that have modest emissions effects at the national level nonetheless have disparate state-level emissions impacts; and (iv) pricing or incentive mechanisms tied to production or consumption will result in markedly different costs to states.

Impact of do-it-yourself air cleaner design on the reduction of simulated wildfire smoke in a controlled chamber environment

During wildfire smoke events public health agencies release advisories to stay indoors, close doors and windows, and operate a portable air cleaner (PAC). The do-it-yourself (DIY) air cleaner consisting of a box fan and a furnace filter is a widely used low-cost alternative to commercial PACs because of its increased accessibility. In this study, we evaluate the clean air delivery rate (CADR) of different DIY air cleaner designs for reducing simulated wildfire smoke and identify operating parameters that may impact their performance and use. The simplest formulation of a DIY air cleaner (box fan with taped on minimum effectiveness reporting value - [MERV] 13 furnace filter) had a CADR of 111.2 ± 1.3 ft3 /min (CFM). Increasing the fan flow by changing the fan type, increasing the fan setting, or reducing the pressure drop across the filtering surface increased the CADR. Large increases in CADR could be obtained by using a shroud (40%), using a 4″ thick filter (123%) using two filters in a wedge shape (137%), or using four filters in a Corsi-Rosenthal (CR) box design (261%). The CADR was greatly reduced with filters heavily loaded with smoke, pointing to the need for frequent filter changes during smoke events.

Air pollutant emissions from global food systems are responsible for environmental impacts, crop losses and mortality

Food systems are important contributors to global emissions of air pollutants. Here, building on the EDGAR-FOOD database of greenhouse gas emissions, we estimate major air pollutant compounds emitted by different stages of the food system, at country level, during the past 50 years, resulting from food production, processing, packaging, transport, retail, consumption and disposal. Air pollutant estimates from food systems include total nitrogen and its components (N₂O, NH₃ and NO_x), SO₂, CO, non-methane volatile organic compounds (NMVOC) and particulate matter (PM₁₀, PM_2.5, black carbon and organic carbon). We show that 10% to 90% of air pollutant emissions come from food systems, resulting from steady increases over the past five decades. In 2018, more than half of total N (and 87% of ammonia) emissions come from food systems and up to 35% of particulate matter. Food system emissions are responsible for about 22.4% of global mortality due to poor air quality and 1.4% of global crop production losses.

How the Air Clean Plan and carbon mitigation measures co-benefited China in PM2.5 reduction and health from 2014 to 2020

China implemented a stringent Air Clean Plan (ACP) since 2013 to address environmental and health risks caused by ambient fine particulate matter (PM_2.5). However, the policy effectiveness of ACP and co-benefits of carbon mitigation measures to environment and health are still largely unknown. Using satellite-based PM_2.5 products produced in our previous study, concentration-response functions, and the logarithmic mean Divisia index (LMDI) method, we analyzed the spatiotemporal dynamics of premature deaths attributable to PM_2.5 exposure, and quantitatively estimated the policy benefits of ACP and carbon mitigation measures. We found the annual PM_2.5 concentrations in China decreased by 33.65 % (13.41 μg m^-3) from 2014 to 2020, accompanied by a decrease in PM_2.5-attributable premature deaths of 0.23 million (95 % confidence interval (CI): 0.22-0.27), indicating the huge benefits of China ACP for human health and environment. However, there were still 1.12 million (95 % CI: 0.79-1.56) premature deaths caused by the exposure of PM_2.5 in mainland China in 2020. Among all ACP measures, clean production (contributed 55.98 % and 51.14 % to decrease in PM_2.5 and premature deaths attributable to PM_2.5) and energy consumption control (contributed 32.58 % and 29.54 % to decrease in PM_2.5 and premature deaths attributable to PM_2.5) made the largest contribution during the past seven years. Nevertheless, the environmental and health benefits of ACP are not fully synergistic in different regions, and the effectiveness of ACP measures reduced from 2018 to 2020. The co-effects of CO₂ and PM_2.5 has become one of the major drivers for PM_2.5 and premature deaths reduction since 2018, confirming the clear environment and health co-benefits of carbon mitigation measures. Our study suggests, with the saturation of clean production and source control, more targeted region-specific strategies and synergistic air pollution-carbon mitigation measures are critical to achieving the WHO's Air Quality Guideline target and the UN's Sustainable Development Goal Target in China.

Compositional Constraints are Vital for Atmospheric PM2.5 Source Attribution over India

India experiences some of the highest levels of ambient PM_2.5 aerosol pollution in the world. However, due to the historical dearth of in situ measurements, chemical transport models that are often used to estimate PM_2.5 exposure over the region are rarely evaluated. Here, we conduct a novel model comparison with speciated airborne measurements of fine aerosol, revealing large biases in the ammonium and nitrate simulations. To address this, we incorporate process-level changes to the model and use satellite observations from the Cross-track Infrared Sounder (CrIS) and the TROPOspheric Monitoring Instrument (TROPOMI) to constrain ammonia and nitrogen oxide emissions. The resulting simulation demonstrates significantly lower bias (NMB_Modified: 0.19; NMB_Base: 0.61) when validated against the airborne aerosol measurements, particularly for the nitrate (NMB_Modified: 0.08; NMB_Base: 1.64) and ammonium simulation (NMB_Modified: 0.49; NMB_Base: 0.90). We use this validated simulation to estimate a population-weighted annual PM_2.5 exposure of 61.4 μg m^-3, with the RCO (residential, commercial, and other) and energy sectors contributing 21% and 19%, respectively, resulting in an estimated 961,000 annual PM_2.5-attributable deaths. Regional exposure and sectoral source contributions differ meaningfully in the improved simulation (compared to the baseline simulation). Our work highlights the critical role of speciated observational constraints in developing accurate model-based PM_2.5 aerosol source attribution for health assessments and air quality management in India.

National Exposure Models for Source-Specific Primary Particulate Matter Concentrations Using Aerosol Mass Spectrometry Data

This paper investigates the feasibility of developing national empirical models to predict ambient concentrations of sparsely monitored air pollutants at high spatial resolution. We used a data set of cooking organic aerosol (COA) and hydrocarbon-like organic aerosol (HOA; traffic primary organic PM) measured using aerosol mass spectrometry across the continental United States. The monitoring locations were selected to span the national distribution of land-use and source-activity variables commonly used for land-use regression modeling (e.g., road length, restaurant count, etc.). The models explain about 60% of the spatial variability of the measured data (R² 0.63 for the COA model and 0.62 for the HOA model). Extensive cross-validation suggests that the models are robust with reasonable transferability. The models predict large urban-rural and intra-urban variability with hotspots in urban areas and along the road corridors. The predicted national concentration surfaces show reasonable spatial correlation with source-specific national chemical transport model (CTM) simulations (R²: 0.45 for COA, 0.4 for HOA). Our measured data, empirical models, and CTM predictions all show that COA concentrations are about two times higher than HOA. Since COA and HOA are important contributors to the intra-urban spatial variability of the total PM_2.5, our results highlight the potential importance of controlling commercial cooking emissions for air quality management in the United States.

Sources of ambient PM2.5 exposure in 96 global cities

To improve air quality, knowledge of the sources and locations of air pollutant emissions is critical. However, for many global cities, no previous estimates exist of how much exposure to fine particulate matter (PM_2.5), the largest environmental cause of mortality, is caused by emissions within the city vs. outside its boundaries. We use the Intervention Model for Air Pollution (InMAP) global-through-urban reduced complexity air quality model with a high-resolution, global inventory of pollutant emissions to quantify the contribution of emissions by source type and location for 96 global cities. Among these cities, we find that the fraction of PM_2.5 exposure caused by within-city emissions varies widely (μ = 37%; σ = 22%) and is not well-explained by surrounding population density. The list of most-important sources also varies by city. Compared to a more mechanistically detailed model, InMAP predicts urban measured concentrations with lower bias and error but also lower correlation. Predictive accuracy in urban areas is not particularly high with either model, suggesting an opportunity for improving global urban air emission inventories. We expect the results herein can be useful as a screening tool for policy options and, in the absence of available resources for further analysis, to inform policy action to improve public health.

Increasing life expectancy in China by achieving its 2025 air quality target

China is striving to build a "Beautiful China" characterized by clean air. The country has committed to further reducing its national mean fine particle (PM2.5) concentration by 10% from 2020 to 2025, following the substantial improvements in its air quality during the past decade. Meanwhile, the "Healthy China" mission has pledged to increase the national mean life expectancy by one year during the same period. Yet, to what extent will the "Beautiful China" mission contribute to the "Healthy China" vision by reducing the levels of the detrimental PM2.5 is still unclear. Here, by coupling the life table approach and an epidemiological concentration-response model, this study quantifies the potential benefits of achieving China's 2025 air quality target on the national life expectancy. The analysis reveals that the Chinese citizen could expect to extend the average life expectancy by 42.5 days by 2025 due to improved air quality. In addition, if the Chinese government outperforms the planned air quality target, as it usually does, the gains would increase to 65.4 days, ∼18% of the "Healthy China" life expectancy increment task. Further reductions in PM2.5 concentration would lead to accelerated gains in life expectancy both nationally and at the city level, providing strong incentives for the authorities to keep improving air quality. This study reveals the notable benefits on individual life that could be expected from air quality improvement in China and suggests that longer life expectancy is achievable by implementing a health-prioritized air quality management mechanism.

Source apportionment, identification and characterization, and emission inventory of ambient particulate matter in 22 Eastern Mediterranean Region countries: A systematic review and recommendations for good practice

Little is known about the main sources of ambient particulate matter (PM) in the 22 Eastern Mediterranean Region (EMR) countries. We designed this study to systematically review all published and unpublished source apportionment (SA), identification and characterization studies as well as emission inventories in the EMR. Of 440 articles identified, 82 (11 emission inventory ones) met our inclusion criteria for final analyses. Of 22 EMR countries, Iran with 30 articles had the highest number of studies on source specific PM followed by Pakistan (n = 15 articles) and Saudi Arabia (n = 8 papers). By contrast, there were no studies in Afghanistan, Bahrain, Djibouti, Libya, Somalia, Sudan, Syria, Tunisia, United Arab Emirates and Yemen. Approximately 72% of studies (51) were published within a span of 2015-2021.48 studies identified the sources of PM_2.5 and its constituents. Positive matrix factorization (PMF), principal component analysis (PCA) and chemical mass balance (CMB) were the most common approaches to identify the source contributions of ambient PM. Both secondary aerosols and dust, with 12-51% and 8-80% (33% and 30% for all EMR countries, on average) had the greatest contributions in ambient PM_2.5. The remaining sources for ambient PM_2.5, including mixed sources (traffic, industry and residential (TIR)), traffic, industries, biomass burning, and sea salt were in the range of approximately 4-69%, 4-49%, 1-53%, 7-25% and 3-29%, respectively. For PM₁₀, the most dominant source was dust with 7-95% (49% for all EMR countries, on average). The limited number of SA studies in the EMR countries (one study per approximately 9.6 million people) in comparison to Europe and North America (1 study per 4.3 and 2.1 million people respectively) can be augmented by future studies that will provide a better understanding of emission sources in the urban environment.

Analysis of the impact of success on three dimensions of sustainability in 173 countries

The United Nations have announced 17 Sustainable Development Goals and 169 targets, which are indivisible and integrated, and which balance the economic, social, and environmental dimensions of sustainable development. This indicates that the performance of successful nations is generally good across many sustainability indicators. Our results, based on multi-criteria and statistical analysis across 173 countries, suggest an interconnection between a country’s sustainability 12 indicators and success. This article focuses on the Country Success and Sustainability (CSS) Maps and Models of the World, which show that improvements in environmental, social, and economic sustainability indicators lead to improvements in the country's success, and vice versa. The CSS Models explain 98.2% of national success and 80.8% of the three dimensions of average sustainability dispersions. When a nation’s success increases by 1%, the 12 indicators of the three dimensions of sustainability improve by 0.85% on average. The human development index and GDP per capita were the success variables with the most substantial impact on 12 sustainability indicators in 173 countries. Calculations made using equal and different weights of 17 criteria show a deviation of 5.34% for the priorities of these 173 countries.

Health burden and economic loss attributable to ambient PM2.5 in Iran based on the ground and satellite data

We estimated mortality and economic loss attributable to PM_2·5 air pollution exposure in 429 counties of Iran in 2018. Ambient PM_2.5-related deaths were estimated using the Global Exposure Mortality Model (GEMM). According to the ground-monitored and satellite-based PM_2.5 data, the annual mean population-weighted PM_2·5 concentrations for Iran were 30.1 and 38.6 μg m^-3, respectively. We estimated that long-term exposure to ambient PM_2.5 contributed to 49,303 (95% confidence interval (CI) 40,914-57,379) deaths in adults ≥ 25 yr. from all-natural causes based on ground monitored data and 58,873 (95% CI 49,024-68,287) deaths using satellite-based models for PM_2.5. The crude death rate and the age-standardized death rate per 100,000 population for age group ≥ 25 year due to ground-monitored PM_2.5 data versus satellite-based exposure estimates was 97 (95% CI 81-113) versus 116 (95% CI 97-135) and 125 (95% CI 104-145) versus 149 (95% CI 124-173), respectively. For ground-monitored and satellite-based PM_2.5 data, the economic loss attributable to ambient PM_2.5-total mortality was approximately 10,713 (95% CI 8890-12,467) and 12,792.1 (95% CI 10,652.0-14,837.6) million USD, equivalent to nearly 3.7% (95% CI 3.06-4.29) and 4.3% (95% CI 3.6-4.5.0) of the total gross domestic product in Iran in 2018.

Impacts of Sugarcane Fires on Air Quality and Public Health in South Florida

BACKGROUND

Preharvest burning of sugarcane is a common agricultural practice in Florida, which produces fine particulate matter [particulate matter (PM) with aerodynamic diameter ≤2.5μm (PM2.5)] that is associated with higher mortality.

OBJECTIVES

We estimated premature mortality associated with exposure to PM2.5 from sugarcane burning in people age 25 y and above for 20 counties in South Florida.

METHODS

We combined information from an atmospheric dispersion model, satellites, and surface measurements to quantify PM2.5 concentrations in South Florida and the fraction of PM2.5 from sugarcane fires. From these concentrations, estimated mortalities attributable to PM2.5 from sugarcane fires were calculated by census tract using health impact functions derived from literature for six causes of death linked to PM2.5. Confidence intervals (CI) are provided based on Monte Carlo simulations that propagate uncertainty in the emissions, dispersion model, health impact functions, and demographic data.

RESULTS

Sugarcane fires emitted an amount of primary PM2.5 similar to that of motor vehicles in Florida. PM2.5 from sugarcane fires is estimated to contribute to mortality rates within the Florida Sugarcane Growing Region (SGR) by 0.4 death per 100,000 people per year (95% CI: 0.3, 1.6 per 100,000). These estimates imply 2.5 deaths per year across South Florida were associated with PM2.5 from sugarcane fires (95% CI: 1.2, 6.1), with 0.16 in the SGR (95% CI: 0.09, 0.6) and 0.72 in Palm Beach County (95% CI: 0.17, 2.2).

DISCUSSION

PM2.5 from sugarcane fires was estimated to contribute to mortality risk across South Florida, particularly in the SGR. This is consistent with prior studies that documented impacts of sugarcane fire on air quality but did not quantify mortality. Additional health impacts of sugarcane fires, which were not quantified here, include exacerbating nonfatal health conditions such as asthma and cardiovascular problems. Harvesting sugarcane without field burning would likely reduce PM2.5 and health burdens in this region. https://doi.org/10.1289/EHP9957.

What you see is what you breathe? Estimating air pollution spatial variation using street level imagery

High spatial resolution information on urban air pollution levels is unavailable in many areas globally, partially due to high input data needs of existing estimation approaches. Here we introduce a computer vision method to estimate annual means for air pollution levels from street level images. We used annual mean estimates of NO2 and PM2.5 concentrations from locally calibrated models as labels from London, New York, and Vancouver to allow for compilation of a sufficiently large dataset (~250k images for each city). Our experimental setup is designed to quantify intra and intercity transferability of image-based model estimates. Performances were high and comparable to traditional land-use regression (LUR) and dispersion models when training and testing on images from the same city (R2 values between 0.51 and 0.95 when validated on data from ground monitoring stations). Like LUR models, transferability of models between cities in different geographies is more difficult. Specifically, transferability between the three cities i.e., London, New York, and Vancouver, which have similar pollution source profiles were moderately successful (R2 values between zero and 0.67). Comparatively, performances when transferring models trained on these cities with very different source profiles i.e., Accra in Ghana and Hong Kong were lower (R2 between zero and 0.21) suggesting the need for local calibration with local calibration using additional measurement data from cities that share similar source profiles.

Impact of Circular, Waste-Heat Reuse Pathways on PM2.5-Air Quality, CO2 Emissions, and Human Health in India: Comparison with Material Exchange Potential

India is home to 1.3 billion people who are exposed to some of the highest levels of ambient air pollution in the world. In addition, India is one of the fastest-growing carbon-emitting countries. Here, we assess how two strategies to reuse waste-heat from coal-fired power plants and other large sources would impact PM_2.5-air quality, human health, and CO₂ emissions in 2015 and a future year, 2050, using varying levels of policy adoption (current regulations, proposed single-sector policies, and ambitious single-sector strategies). We find that power plant and industrial waste-heat reuse as input to district heating systems (DHSs), a novel, multisector strategy to reduce local biomass burning for heating emissions, can offset 71.3-85.2% of residential heating demand in communities near a power plant (9.3-12.4% of the nationwide heating demand) with the highest benefits observed during winter months in areas with collocated industrial activity and higher residential heating demands (e.g., New Delhi). Utilizing waste-heat to generate electricity via organic Rankine cycles (ORCs) can generate an additional 22 (11% of total coal-fired generating capacity), 41 (8%), 32 (13%), and 6 (5%) GW of electricity capacity in the 2015, 2050-current regulations, 2050-single-sector, and 2050-ambitious-single-sector scenarios, respectively. Emission estimates utilizing these strategies were input to the GEOS-Chem model, and population-weighted, simulated PM_2.5 showed small improvements in the DHS (0.2-0.4%) and ORC (0.3-3.4%) scenarios, where the minimal DHS PM_2.5-benefit is attributed to the small contribution of biomass burning for heating to nationwide PM_2.5 emissions (much of the biomass burning activity is for cooking). The PM_2.5 reductions lead to ∼130-36,000 mortalities per year avoided among the scenarios, with the largest health benefits observed in the ORC scenarios. Nationwide CO₂ emissions reduced <0.04% by DHSs but showed larger reductions using ORCs (1.9-7.4%). Coal fly-ash as material exchange in cement and brick production was assessed, and capacity exists to completely reutilize unused fly-ash toward cement and brick production in each of the scenarios.

Source Sector Mitigation of Solar Energy Generation Losses Attributable to Particulate Matter Pollution

Particulate matter (PM) in the atmosphere and deposited on solar photovoltaic (PV) panels reduce PV energy generation. Reducing anthropogenic PM sources will therefore increase carbon-free energy generation and as a cobenefit will improve surface air quality. However, we lack a global understanding of the sectors that would be the most effective at achieving the necessary reductions in PM sources. Here we combine well-evaluated models of solar PV performance and atmospheric composition to show that deep cuts in air pollutant emissions from the residential, on-road, and energy sectors are the most effective approaches to mitigate PM-induced PV energy losses over East and South Asia, and the Tibetan Plateau, Central Asia, and the Arabian Peninsula, and Western Siberia, respectively. Using 2019 PV capacities as a baseline, we find that a 50% reduction in residential emissions would lead to an additional 10.3 TWh yr^-1 (US$878 million yr^-1) and 2.5 TWh yr^-1 (US$196 million yr^-1) produced in China and India, respectively.

Influence of Spatial Resolution on Satellite-Based PM2.5 Estimation: Implications for Health Assessment

Satellite-based PM2.5 estimation has been widely used to assess health impact associated with PM2.5 exposure and might be affected by spatial resolutions of satellite input data, e.g., aerosol optical depth (AOD). Here, based on Multi-Angle Implementation of Atmospheric Correction (MAIAC) AOD in 2020 over the Yangtze River Delta (YRD) and three PM2.5 retrieval models, i.e., the mixed effects model (ME), the land-use regression model (LUR) and the Random Forest model (RF), we compare these model performances at different spatial resolutions (1, 3, 5 and 10 km). The PM2.5 estimations are further used to investigate the impact of spatial resolution on health assessment. Our cross-validated results show that the model performance is not sensitive to spatial resolution change for the ME and LUR models. By contrast, the RF model can create a more accurate PM2.5 prediction with a finer AOD spatial resolution. Additionally, we find that annual population-weighted mean (PWM) PM2.5 concentration and attributable mortality strongly depend on spatial resolution, with larger values estimated from coarser resolution. Specifically, compared to PWM PM2.5 at 1 km resolution, the estimation at 10 km resolution increases by 7.8%, 22.9%, and 9.7% for ME, LUR, and RF models, respectively. The corresponding increases in mortality are 7.3%, 18.3%, and 8.4%. Our results also show that PWM PM2.5 at 10 km resolution from the three models fails to meet the national air quality standard, whereas the estimations at 1, 3 and 5 km resolutions generally meet the standard. These findings suggest that satellite-based health assessment should consider the spatial resolution effect.

Updated World Health Organization Air Quality Guidelines Highlight the Importance of Non-anthropogenic PM2.5

The World Health Organization recently updated their air quality guideline for annual fine particulate matter (PM_2.5) exposure from 10 to 5 μg m^-3, citing global health considerations. We explore if this guideline is attainable across different regions of the world using a series of model sensitivity simulations for 2019. Our results indicate that >90% of the global population is exposed to PM_2.5 concentrations that exceed the 5 μg m^-3 guideline and that only a few sparsely populated regions (largely in boreal North America and Asia) experience annual average concentrations of <5 μg m^-3. We find that even under an extreme abatement scenario, with no anthropogenic emissions, more than half of the world's population would still experience annual PM_2.5 exposures above the 5 μg m^-3 guideline (including >70% and >60% of the African and Asian populations, respectively), largely due to fires and natural dust. Our simulations demonstrate the large heterogeneity in PM_2.5 composition across different regions and highlight how PM_2.5 composition is sensitive to reductions in anthropogenic emissions. We thus suggest the use of speciated aerosol exposure guidelines to help facilitate region-specific air quality management decisions and improve health-burden estimates of fine aerosol exposure.

Mortality Attributable to Long-Term Exposure to Ambient Fine Particulate Matter: Insights from the Epidemiologic Evidence for Understudied Locations

Epidemiologic cohort studies have consistently demonstrated that long-term exposure to ambient fine particles (PM_2.5) is associated with mortality. Nevertheless, extrapolating results to understudied locations may involve considerable uncertainty. To explore this issue, this review discusses the evidence for (i) the associated risk of mortality, (ii) the shape of the concentration-response function, (iii) a causal interpretation, and (iv) how the source mix/composition of PM_2.5 and population characteristics may alter the effect. The accumulated evidence suggests the following: (i) In the United States, the change in all-cause mortality risk per μg/m³ is about 0.8%. (ii) The concentration-response function appears nonlinear. (iii) Causation is overwhelmingly supported. (iv) Fossil fuel combustion-related sources are likely more toxic than others, and age, race, and income may modify the effect. To illustrate the use of our findings in support of a risk assessment in an understudied setting, we consider Kuwait. However, given the complexity of this relationship and the heterogeneity in reported effects, it is unreasonable to think that, in such circumstances, point estimates can be meaningful. Consequently, quantitative probabilistic estimates, which cannot be derived objectively, become essential. Formally elicited expert judgment can provide such estimates, and this review provides the evidence to support an elicitation.

Source identification and health risk assessments of heavy metals in indoor dusts of Ilorin, North central Nigeria

BACKGROUND AND PURPOSE

Exposure to heavy metals (HMs) in indoor dusts is a serious public concern that is linked to a myriad of deleterious health outcomes. The objectives of this study are to estimate the contamination levels of HMs in indoor dusts of different residential areas in Ilorin, Nigeria; identify HMs sources in different residential areas; and evaluate human health risks of HMs in selected residential areas.

METHODS

Indoor dust sampling was conducted in ten randomly selected from low, medium and high population density residential areas of Ilorin, Nigeria. Ten HMs concentration levels, their health risk implication and the associated potential ecological risks were evaluated.

RESULTS

The mean concentration levels measured for Fe, Pb, Zn, As, Co, Cr, Cu, Cd, Mn and Ni were 38.99, 5.74, 3.99, 0.08, 2.82, 2.13, 0.47, 0.60, 6.45 and 1.09 mg/kg, respectively. Positive Matrix Factorization (PMF) model was applied to ascertain sources of HMs in sampled indoor dust. Percentage contribution from oil-based cooking (29.82%) and transportation (29.77%) represented the highest source to HM concentrations among the six factors identified. The results of the various pollution indices employed showed that Pb, Zn, As, Co, Cr, Cu, Mn and Ni contributed moderately to HMs concentration levels in the sampled dusts. Cd had highest potential ecological risk factor E r i of between 160 and 320. The average values of Enrichment Factors (EFs) obtained aside from Fe used as the reference metal, ranged between 8.46 (As) and 2521.61(Cd). Health risk assessment results revealed that children are the most susceptible to the risks associated with HMs bound indoor dust than the adults. The percentage risk contributions of Hazard Quotient via ingestion route (HQ_ing) in Hazard Index (HI) for non-cancer risk of indoor HMs were 93.17% and 69.87% in children and adults, respectively. Likewise, the percentage cancer risks contribution through ingestion pathway (CR_ing) were higher than cancer risks through inhalation and dermal pathways (CR_inh and CR_dermal), accounting for 99.84% and 97.04% of lifetime cancer risk in children and adults, respectively. The contamination level of Cd recorded is of great concern and signifies very strong contribution from anthropogenic sources.

CONCLUSION

This study has further revealed the levels of HMs in typical African residential settings that could be used by relevant stakeholders and policy makers in developing lasting control measures.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s40201-021-00778-8.

Emission Sector Impacts on Air Quality and Public Health in China From 2010 to 2020

Anthropogenic emissions and ambient fine particulate matter (PM2.5) concentrations have declined in recent years across China. However, PM2.5 exposure remains high, ozone (O3) exposure is increasing, and the public health impacts are substantial. We used emulators to explore how emission changes (averaged per sector over all species) have contributed to changes in air quality and public health in China over 2010-2020. We show that PM2.5 exposure peaked in 2012 at 52.8 μg m-3, with contributions of 31% from industry and 22% from residential emissions. In 2020, PM2.5 exposure declined by 36% to 33.5 μg m-3, where the contributions from industry and residential sources reduced to 15% and 17%, respectively. The PM2.5 disease burden decreased by only 9% over 2012 where the contributions from industry and residential sources reduced to 15% and 17%, respectively 2020, partly due to an aging population with greater susceptibility to air pollution. Most of the reduction in PM2.5 exposure and associated public health benefits occurred due to reductions in industrial (58%) and residential (29%) emissions. Reducing national PM2.5 exposure below the World Health Organization Interim Target 2 (25 μg m-3) would require a further 80% reduction in residential and industrial emissions, highlighting the challenges that remain to improve air quality in China.

Nationwide and Regional PM2.5-Related Air Quality Health Benefits From the Removal of Energy-Related Emissions in the United States

Clean energy policy can provide substantial health benefits through improved air quality. As ambitious clean energy proposals are increasingly considered and adopted across the United States (US), quantifying the benefits of removal of such large air pollution emissions sources is crucial to understanding potential societal impacts of such policy. In this study, we estimate health benefits resulting from the elimination of emissions of fine particulate matter (PM_2.5), sulfur dioxide, and nitrogen oxides from the electric power, transportation, building, and industrial sectors in the contiguous US. We use EPA's CO-Benefits Risk Assessment screening tool to estimate health benefits resulting from the removal of PM_2.5-related emissions from these energy-related sectors. We find that nationwide efforts to eliminate energy-related emissions could prevent 53,200 (95% CI: 46,900-59,400) premature deaths each year and provide $608 billion ($537-$678 billion) in benefits from avoided PM_2.5-related illness and death. We also find that an average of 69% (range: 32%-95%) of the health benefits from emissions removal remain in the emitting region. Our study provides an indication of the potential scale and distribution of public health benefits that could result from ambitious regional and nationwide clean energy and climate mitigation policy.

Measuring and predicting personal and household Black Carbon levels from 88 communities in eight countries

Black Carbon (BC) is an important component of household air pollution (HAP) in low- and middle- income countries (LMICs), but levels and drivers of exposure are poorly understood. As part of the Prospective Urban and Rural Epidemiological (PURE) study, we analyzed 48-hour BC measurements for 1187 individual and 2242 household samples from 88 communities in 8 LMICs (Bangladesh, Chile, China, Colombia, India, Pakistan, Tanzania, and Zimbabwe). Light absorbance (10^-5 m^-1) of collected PM_2.5 filters, a proxy for BC concentrations, was calculated via an image-based reflectance method. Surveys of household/personal characteristics and behaviors were collected after monitoring. The geometric mean (GM) of personal and household BC measures was 2.4 (3.3) and 3.5 (3.9)·10^-5 m^-1, respectively. The correlation between BC and PM_2.5 was r = 0.76 for personal and r = 0.82 for household measures. A gradient of increasing BC concentrations was observed for cooking fuels: BC increased 53% (95%CI: 30, 79) for coal, 142% (95%CI: 117, 169) for wood, and 190% (95%CI: 149, 238) for other biomass, compared to gas. Each hour of cooking was associated with an increase in household (5%, 95%CI: 3, 7) and personal (5%, 95%CI: 2, 8) BC; having a window in the kitchen was associated with a decrease in household (-38%, 95%CI: -45, -30) and personal (-31%, 95%CI: -44, -15) BC; and cooking on a mud stove, compared to a clean stove, was associated with an increase in household (125%, 95%CI: 96, 160) and personal (117%, 95%CI: 71, 117) BC. Male participants only had slightly lower personal BC (-0.6%, 95%CI: -1, 0.0) compared to females. In multivariate models, we were able to explain 46-60% of household BC variation and 33-54% of personal BC variation. These data and models provide new information on exposure to BC in LMICs, which can be incorporated into future exposure assessments, health research, and policy surrounding HAP and BC.

Rapid rise in premature mortality due to anthropogenic air pollution in fast-growing tropical cities from 2005 to 2018

Tropical cities are experiencing rapid growth but lack routine air pollution monitoring to develop prescient air quality policies. Here, we conduct targeted sampling of recent (2000s to 2010s) observations of air pollutants from space-based instruments over 46 fast-growing tropical cities. We quantify significant annual increases in nitrogen dioxide (NO₂) (1 to 14%), ammonia (2 to 12%), and reactive volatile organic compounds (1 to 11%) in most cities, driven almost exclusively by emerging anthropogenic sources rather than traditional biomass burning. We estimate annual increases in urban population exposure to air pollutants of 1 to 18% for fine particles (PM_2.5) and 2 to 23% for NO₂ from 2005 to 2018 and attribute 180,000 (95% confidence interval: -230,000 to 590,000) additional premature deaths in 2018 (62% increase relative to 2005) to this increase in exposure. These cities are predicted to reach populations of up to 80 million people by 2100, so regulatory action targeting emerging anthropogenic sources is urgently needed.

A comprehensive high-resolution gridded emission inventory of anthropogenic sources of air pollutants in Indian megacity Kolkata

Abstract

In this study, we present a first-ever effort made to develop an ultra-high-resolution gridded emission inventory (i.e. ~ 0.4 km ×  ~ 0.4 km) for the Indian megacity Kolkata. As the rising demand for fossil fuels based energy along with the spread of urban corridors have forced the anthropogenic activities to a mounting level, therefore determining the sources responsible is of paramount importance. This has worsened not only the regional air quality but also has an indirect effect on the global air quality. The spatial and temporal variation of the source requires an accurate estimation of the surface emission which is the most essential parameter to study the air quality, that positively has been fulfilled in this study. The annual emission for 2020 is calculated to be 37.2 Gg/yr of PM2.5, 61.4 Gg/yr of PM10, 222.6 Gg/yr of CO, 131.3 Gg/yr of NOx, 60.3 Gg/yr of SO2, 120.4 Gg/yr of VOC, 9.5 Gg/yr of BC and 16.8 Gg/yr of OC that prevails in the toxic air of megacity Kolkata. The present surface chemistry dataset will be the first line of detailed information regarding emission hotspots in the megacity that could be used as important tool for clean air mitigation strategies, input into the air quality modeling study to tackle environmental issues, and public health.

Article Highlights

Designing health impact functions to assess marginal changes in outdoor fine particulate matter

Estimating health benefits from improvements in ambient air quality requires the characterization of the magnitude and shape of the association between marginal changes in exposure and marginal changes in risk, and its uncertainty. Several attempts have been made to do this, each requiring different assumptions. These include the Log-Linear(LL), IntegratedExposure-Response(IER), and GlobalExposureMortalityModel(GEMM). In this paper we develop an improved relative risk model suitable for use in health benefits analysis that incorporates features of existing models while addressing limitations in each model. We model the derivative of the relative risk function within a meta-analytic framework; a quantity directly applicable to benefits analysis, incorporating a Fusion of algebraic functions used in previous models. We assume a constant derivative in concentration over low exposures, like the LL model, a declining derivative over moderate exposures observed in cohort studies, and a derivative declining as the inverse of concentration over high global exposures in a similar manner to the GEMM. The model properties are illustrated with examples of fitting it to data for the six specific causes of death previously examined by the GlobalBurdenofDisease program with ambient fine particulate matter (PM_2.5). In a test case analysis assuming a 1% (benefits analysis) or 100% (burden analysis), reduction in country-specific fine particulate matter concentrations, corresponding estimated global attributable deaths using the Fusion model were found to lie between those of the IER and LL models, with the GEMM estimates similar to those based on the LL model.

Microplastics in Asian freshwater ecosystems: Current knowledge and perspectives

Plastic pollution in freshwater ecosystems, including microplastics (MPs) smaller than 5 mm, has become an emerging global concern. Asia is considered a "hot spot" for plastic pollution due to rapid economic and demographic growth, together with rapid urbanization. Here, we provide an overview of the current knowledge on MP abundance, sources, fate, and transfer in Asian freshwater ecosystems based on publications from January 2014 to May 2021. MP contamination in freshwater compartments, including water, sediment, and biota, was found to vary strongly. In water, it ranged from 0.004 items m^-3 in a moderately urbanized region to more than 500,000 items m^-3 in a dumping river in a highly populated watershed. In the sediment, MP abundance ranged from 1 to more than 30,000 items kg^-1 dry weight. Polyethylene (PE) and polypropylene (PP) were predominant in both water and sediment compartments. MP was detected in biota samples from all the studied species, but their abundance depended on the locations and species studied. Overall, MP characteristics (form, size, color, and polymer type) depended on sources and natural constraints (mainly hydrodynamics). This study also revealed that MP in Asian freshwater ecosystems mainly originated from domestic wastewater/runoff, followed by industrial emissions, fisheries and aquaculture wastewater. Plastic waste is not efficiently recycled or incinerated in Asia, leading to MP transfer and accumulation in the aquatic environment, and, more importantly, to ingestion by low to high trophic level organisms. This work highlights several knowledge gaps to guides future research to improve MP pollution management for the sustainable development of highly populated regions such as Asia.

Spatial-Temporal Evolution of Health Impact and Economic Loss upon Exposure to PM2.5 in China

Exposure to PM_2.5 can seriously endanger public health. Policies for controlling PM_2.5 need to consider health hazards under different circumstances. Unlike most studies on the concentration, distribution, and influencing factors of PM_2.5, the present study focuses on the impact of PM_2.5 on human health. We analysed the spatial-temporal evolution of health impact and economic loss caused by PM_2.5 exposure using the log-linear exposure-response function and benefit transfer method. The results indicate that the number of people affected by PM_2.5 pollution fluctuated and began to decline after reaching a peak in 2014, benefiting from the Air Pollution Prevention and Control Action Plan. Regarding the total economic loss, the temporal pattern continued to rise until 2014 and then declined, with an annual mean of 86,886.94 million USD, accounting for 1.71% of China’s GDP. For the spatial pattern, the health impact and economic loss show a strong spatial correlation and remarkable polarisation phenomena, with high values in East China, North China, Central China, and South China, but low values in Southwest China, Northwest China, and Northeast China. The spatial-temporal characterisation of PM_2.5 health hazards is visualised and analysed accordingly, which can provide a reference for more comprehensive and effective policy decisions.

Global health burden of ambient PM2.5 and the contribution of anthropogenic black carbon and organic aerosols

Chronic exposure to fine particulate matter (PM_2.5) poses a major global health risk, commonly assessed by assuming equivalent toxicity for different PM_2.5 constituents. We used a data-informed global atmospheric model and recent exposure-response functions to calculate the health burden of ambient PM_2.5 from ten source categories. We estimate 4.23 (95% confidence interval 3.0-6.14) million excess deaths annually from the exposure to ambient PM_2.5. We distinguished contributions and major sources of black carbon (BC), primary organic aerosols (POA) and anthropogenic secondary organic aerosols (aSOA). These components make up to ∼20% of the total PM_2.5 in South and East Asia and East Africa. We find that domestic energy use by the burning of solid biofuels is the largest contributor to ambient BC, POA and aSOA globally. Epidemiological and toxicological studies indicate that these compounds may be relatively more hazardous than other PM_2.5 compounds such as soluble salts, related to their high potential to inflict oxidative stress. We performed sensitivity analyses by considering these species to be more harmful compared to other compounds in PM_2.5, as suggested by their oxidative potential using a range of potential relative risks. These analyses show that domestic energy use emerges as the leading cause of excess mortality attributable to ambient PM_2.5, notably in Asia and Africa. We acknowledge the uncertainties inherent in our assumed enhanced toxicity of the anthropogenic organic and BC aerosol components, which suggest the need to better understand the mechanisms and magnitude of the associated health risks and the consequences for regulatory policies. However our assessment of the importance of emissions from domestic energy use as a cause of premature mortality is robust to a range of assumptions about the magnitude of the excess risk.

Mechanisms and Pathways for Coordinated Control of Fine Particulate Matter and Ozone

PURPOSE OF REVIEW

Fine particulate matter (PM_2.5) and ground-level ozone (O₃) pose a significant risk to human health. The World Health Organization (WHO) has recently revised healthy thresholds for both pollutants. The formation and evolution of PM_2.5 and O₃ are however governed by complex physical and multiphase chemical processes, and therefore, it is extremely challenging to mitigate both pollutants simultaneously. Here, we review mechanisms and discuss the science-informed pathways for effective and simultaneous mitigation of PM_2.5 and O₃.

RECENT FINDINGS

Global warming has led to a general increase in biogenic emissions, which can enhance the formation of O₃ and secondary organic aerosols. Reductions in anthropogenic emissions during the COVID-19 lockdown reduced PM_2.5; however, O₃ was enhanced in several polluted regions. This was attributed to more intense sunlight due to low aerosol loading and non-linear response of O₃ to NO _x . Such contrasting physical and chemical interactions hinder the formulation of a clear roadmap for clean air over such regions.

SUMMARY

Atmospheric chemistry including the role of biogenic emissions, aerosol-radiation interactions, boundary layer, and regional-scale transport are the key aspects that need to be carefully considered in the formulation of mitigation pathways. Therefore, a thorough understanding of the chemical effects of the emission reductions, changes in photolytic rates and boundary layer due to perturbation of solar radiation, and the effect of meteorological/seasonal changes are needed on a regional basis. Statistical emulators and machine learning approaches can aid the cumbersome process of multi-sector multi-species source attribution.

Global Burden of Disease from Major Air Pollution Sources (GBD MAPS): A Global Approach

Ambient fine particulate matter (particles <2.5 μm in aerodynamic diameter [PM2.5]) is the world's leading environmental health risk factor. Reducing the PM2.5 disease burden requires specific strategies that target dominant sources across multiple spatial scales. The Global Burden of Disease from Major Air Pollution Sources (GBD MAPS) project provides a contemporary and comprehensive evaluation of contributions to the ambient PM2.5 disease burden from source sectors and fuels across 21 regions, 204 countries, and 200 subnational areas. We first derived quantitative contributions from 24 emission sensitivity simulations using an updated global atmospheric chemistry-transport model, input with a newly developed detailed anthropogenic emissions dataset that includes emissions specific to source sector and fuels. These simulation results were integrated with newly available high-resolution satellite-derived PM2.5 exposure estimates and disease-specific concentration-response relationships consistent with the GBD project to quantify contributions of specific source sector and fuel to the ambient PM2.5 disease burden across all regions, countries, and subnational areas. To improve the transparency and reproducibility of this and future work, we publicly provided the global atmospheric chemistry-transport model source code, emissions dataset and emissions model source code, analysis scripts, and source sensitivity results, and further described the emissions dataset and source contribution results in two publications.

We found that nearly 1.05 million (95% uncertainty interval [UI]: 0.74-1.36 million) deaths worldwide (27.3% of the total mortality attributable to PM2.5) would be avoidable by eliminating fossil fuel combustion, with coal contributing over half of that burden. Residential (19.2%; 736,000 deaths [95% UI: 521,000-955,000]), industrial (11.7%; 448,000 deaths [95% UI: 318,000-582,000]), and energy (10.2%; 391,000 deaths [95% UI: 277,000-507,000]) sector emissions are among the dominant global sources Uncertainty in these estimates reflects those of the input datasets. Regions with the largest anthropogenic contributions generally have the highest numbers of attributable deaths, which clearly demonstrates the importance of reducing these emissions to realize reductions in global air pollution and its disease burden.

Source identification and health risk assessments of polycyclic aromatic hydrocarbons in settled dusts from different population density areas of Ilorin, Nigeria

Polycyclic aromatic hydrocarbons (PAHs) have attracted significant attention in recent times on account of their reasonably high environmental burden and extreme toxicity. Samples of indoor dusts were obtained daily over a period of 2 weeks from 10 residences located within low, medium, and high density residential areas of Ilorin City. The concentration levels, potential sources, and cancer health risks of sixteen polycyclic aromatic hydrocarbons (PAHs) were investigated using gas chromatography/mass spectrometry. PAHs total concentrations varied from 3.95 ± 0.19 to 8.70 ± 0.43 μg/g with arithmetic mean of 6.09 ± 0.46 μg/g. Fluoranthene was the most dominant PAHs congener. High molecular weight (HMW) PAHs (4-6 rings) were the most prevalent PAHs and were responsible for 79.29% of total PAHs in sampled residences. Chrysene (Chry) was the most abundant compound among the 7 carcinogenic PAHs (CPAHs). Moreover, diagnostic ratios and positive matrix factorization (PMF) employed to apportion PAHs suggested that indoor dusts originated from indoor activities and infiltrating outdoor air pollutants. Diagnostic ratios revealed that PAHs are from mixed sources which include coal/wood combustion, non-traffic and traffic emissions, petroleum, petrogenic (gasoline), and petroleum combustion. Similarly, positive matrix factorization (PMF) model suggested five sources (factors) were responsible for PAHs in indoor dusts comprised of petroleum combustion and traffic emissions (60.05%), wood and biomass combustion emissions (20.84%), smoke from cooking, incense burning and tobacco (4.17%), gasoline combustion from non-traffic sources (13.89%), and emissions from coal burning and electronic devices (1.05%). The incremental lifetime carcinogenic risks (ILCR) of PAHs in adults and children estimated by applying benzo(a)pyrene (BaP) equivalent were within the satisfactory risk limits in Ilorin. Indoor PAHs emissions in Ilorin residences could be monitored and controlled by using data provided in this study.

Source Apportionment of Fine Organic Particulate Matter (PM2.5) in Central Addis Ababa, Ethiopia

The development of infrastructure, a rapidly increasing population, and urbanization has resulted in increasing air pollution levels in the African city of Addis Ababa. Prior investigations into air pollution have not yet sufficiently addressed the sources of atmospheric particulate matter. This study aims to identify the major sources of fine particulate matter (PM2.5) and its seasonal contribution in Addis Ababa, Ethiopia. Twenty-four-hour average PM2.5 mass samples were collected every 6th day, from November 2015 through November 2016. Chemical species were measured in samples and source apportionment was conducted using a chemical mass balance (CMB) receptor model that uses particle-phase organic tracer concentrations to estimate source contributions to PM2.5 organic carbon (OC) and the overall PM2.5 mass. Vehicular sources (28%), biomass burning (18.3%), plus soil dust (17.4%) comprise about two-thirds of the PM2.5 mass, followed by sulfate (6.5%). The sources of air pollution vary seasonally, particularly during the main wet season (June-September) and short rain season (February-April): From motor vehicles, (31.0 ± 2.6%) vs. (24.7 ± 1.2%); biomass burning, (21.5 ± 5%) vs. (14 ± 2%); and soil dust, (11 ± 6.4%) vs. (22.7 ± 8.4%), respectively, are amongst the three principal sources of ambient PM2.5 mass in the city. We suggest policy measures focusing on transportation, cleaner fuel or energy, waste management, and increasing awareness on the impact of air pollution on the public's health.

Improved Mechanistic Model of the Atmospheric Redox Chemistry of Mercury

We present a new chemical mechanism for Hg⁰/Hg^I/Hg^II atmospheric cycling, including recent laboratory and computational data, and implement it in the GEOS-Chem global atmospheric chemistry model for comparison to observations. Our mechanism includes the oxidation of Hg⁰ by Br and OH, subsequent oxidation of Hg^I by ozone and radicals, respeciation of Hg^II in aerosols and cloud droplets, and speciated Hg^II photolysis in the gas and aqueous phases. The tropospheric Hg lifetime against deposition in the model is 5.5 months, consistent with observational constraints. The model reproduces the observed global surface Hg⁰ concentrations and Hg^II wet deposition fluxes. Br and OH make comparable contributions to global net oxidation of Hg⁰ to Hg^II. Ozone is the principal Hg^I oxidant, enabling the efficient oxidation of Hg⁰ to Hg^II by OH. BrHg^IIOH and Hg^II(OH)₂, the initial Hg^II products of Hg⁰ oxidation, respeciate in aerosols and clouds to organic and inorganic complexes, and volatilize to photostable forms. Reduction of Hg^II to Hg⁰ takes place largely through photolysis of aqueous Hg^II-organic complexes. 71% of model Hg^II deposition is to the oceans. Major uncertainties for atmospheric Hg chemistry modeling include Br concentrations, stability and reactions of Hg^I, and speciation and photoreduction of Hg^II in aerosols and clouds.

Contributions of internal emissions to peaks and incremental indoor PM2.5 in rural coal use households

Indoor air quality is critically important to the human as people spend most time indoors. Indoor PM_2.5 is related to the outdoor levels, but more directly influenced by internal sources. Severe household air pollution from solid fuel use has been recognized as one major risk for human health especailly in rural area, however, the issue is significantly overlooked in most national air quality controls and intervention policies. Here, by using low-cost sensors, indoor PM_2.5 in rural homes burning coals was monitored for ~4 months and analyzed for its temporal dynamics, distributions, relationship with outdoor PM_2.5, and quantitative contributions of internal sources. A bimodal distribution of indoor PM_2.5 was identified and the bimodal characteristic was more significant at the finer time resolution. The bimodal distribution maxima were corresponding to the emissions from strong internal sources and the influence of outdoor PM_2.5, respectively. Indoor PM_2.5 was found to be correlated with the outdoor PM_2.5, even though indoor coal combustion for heating was thought to be predominant source of indoor PM_2.5. The indoor-outdoor relationship differed significantly between the heating and non-heating seasons. Impacts of typical indoor sources like cooking, heating associated with coal use, and smoking were quantitatively analyzed based on the highly time-resolved PM_2.5. Estimated contribution of outdoor PM_2.5 to the indoor PM_2.5 was ~48% during the non-heating period, but decreased to about 32% during the heating period. The contribution of indoor heating burning coals comprised up to 47% of the indoor PM_2.5 during the heating period, while the other indoor sources contributed to ~20%. The study, based on a relatively long-term timely resolved PM_2.5 data from a large number of rural households, provided informative results on temporal dynamics of indoor PM_2.5 and quantitative contributions of internal sources, promoting scientific understanding on sources and impacts of household air pollution.

Toward Clean Residential Energy: Challenges and Priorities in Research

Solid fuels used for cooking, heating, and lighting are major emission sources of many air pollutants, specifically PM_2.5 and black carbon, resulting in adverse environmental and health impacts. At the same time, the transition from using residential solid fuels toward using cleaner energy sources can result in significant health benefits. Here, we briefly review recent research progress on the emissions of air pollutants from the residential sector and the impacts of emissions on ambient and indoor air quality, population exposure, and health consequences. The major challenges and future research priorities are identified and discussed.

Higher Dietary Se Intake Is Associated With the Risk of New-Onset Fracture: A National Longitudinal Study for 20 Years

Background: The association between dietary selenium (Se) intake and osteoporosis-related fractures remains inconsistent. We aimed to examine the dose relationship between Se intake and incident fracture among Chinese adults. Methods: The dietary data were retrieved from the China Health and Nutrition Survey conducted between 1991 and 2011, and 17,150 participants aged above 20 were included. A 3-day, 24-h recall of food intake was performed to assess cumulative average dietary Se intake. The fracture was based on self-report in each survey between 1997 and 2011. The association between Se intake and fracture was tested by Cox regression, and the non-linear association was examined by restricted cubic splines (RCS). Results: There were 976 fracture cases during a mean of 10.2 years follow-up. In a fully adjusted Cox model, across the quartiles of Se intake, the hazard ratios (HRs) for fracture were 1.07 (95% CI .86-1.33), 1 (reference), 1.25 (95% CI 1.02-1.53), and 1.33 (95% CI 1.07-1.65). RCS showed a parabolic association (P non-linear = 0.037) between Se and fracture for men as well as a U-shape dose-response (P non-linear = 0.04) between Se and fracture for subjects living in highly urbanized areas. Conclusion: In conclusion, there is a non-linear association between selenium intake and fracture, with higher intake associated with increased risk. The shape of the association varies by gender and urbanization level.